Adaptive Time-Frequency Segment Optimization for Motor Imagery Classification.

Motor imagery (MI)-based brain-computer interface (BCI) has emerged as a crucial method for rehabilitating stroke patients. However, the variability in the time-frequency distribution of MI-electroencephalography (EEG) among individuals limits the generalizability of algorithms that rely on non-customized time-frequency segments. In this study, we propose a novel method for optimizing time-frequency segments of MI-EEG using the sparrow search algorithm (SSA). Additionally, we apply a correlation-based channel selection (CCS) method that considers the correlation coefficient of features between each pair of EEG channels. Subsequently, we utilize a regularized common spatial pattern method to extract effective features. Finally, a support vector machine is employed for signal classification. The results on three BCI datasets confirmed that our algorithm achieved better accuracy (99.11% vs. 94.00% for BCI Competition III Dataset IIIa, 87.70% vs. 81.10% for Chinese Academy of Medical Sciences dataset, and 87.94% vs. 81.97% for BCI Competition IV Dataset 1) compared to algorithms with non-customized time-frequency segments. Our proposed algorithm enables adaptive optimization of EEG time-frequency segments, which is crucial for the development of clinically effective motor rehabilitation.

Stretchable piezoelectric energy harvesters and self-powered sensors for wearable and implantable devices.

Wearable and implantable bio-integrated electronics have started to gain momentum because of their essential role in improving the quality of life for various patients and healthy individuals. However, their continuous operation is often limited by traditional battery technologies with a limited lifespan, creating a significant challenge for their development. Thus, it is highly desirable to harvest biomechanical energies from human motion for self-powered bio-integrated functional devices. Piezoelectric energy harvesters are ideal candidates to achieve this goal by converting biomechanical energy to electric energy. Because of their applications on soft and highly deformable tissues of the human body, these devices also need to be mechanically flexible and stretchable, thus posing a significant challenge. Effective methods to address the challenge include the exploration of new stretchable piezoelectric materials (e.g., hybrid composite material) and stretchable structures (e.g., buckled shapes, serpentine mesh layouts, kirigami designs, among others). This review presents an overview of the recent developments in new intrinsically stretchable piezoelectric materials and rigid inorganic piezoelectric materials with novel stretchable structures for flexible and stretchable piezoelectric sensors and energy harvesters. Following the discussion of theoretical modeling of the piezoelectric materials to convert mechanical deformations into electrical signals, the representative applications of stretchable piezoelectric materials and structures in wearable and implantable devices are briefly summarized. The present limitations and future research directions of flexible and stretchable piezoelectric devices are then discussed.

Transfer Printing and its Applications in Flexible Electronic Devices.

Flexible electronic systems have received increasing attention in the past few decades because of their wide-ranging applications that include the flexible display, eyelike digital camera, skin electronics, and intelligent surgical gloves, among many other health monitoring devices. As one of the most widely used technologies to integrate rigid functional devices with elastomeric substrates for the manufacturing of flexible electronic devices, transfer printing technology has been extensively studied. Though primarily relying on reversible interfacial adhesion, a variety of advanced transfer printing methods have been proposed and demonstrated. In this review, we first summarize the characteristics of a few representative methods of transfer printing. Next, we will introduce successful demonstrations of each method in flexible electronic devices. Moreover, the potential challenges and future development opportunities for transfer printing will then be briefly discussed.

In situ full-field measurement of surface oxidation on Ni-based alloy using high temperature scanning probe microscopy.

We use in situ scanning probe microscopy (SPM) to investigate the high temperature oxidation of Ni-based single crystal alloys at the micro-/nanoscale. SiO2 micro-pillar arrays were pre-fabricated on the alloy surface as markers before the oxidation experiment. The SPM measurement of the oxidized surface in the vicinity of SiO2 micro-pillars was conducted real time at temperatures from 300 °C to 800 °C. The full-field evolution of oxide film thickness is quantitatively characterized by using the height of SiO2 micro-pillars as reference. The results reveal the non-uniform oxide growth featuring the nucleation and coalescence of oxide islands on the alloy surface. The outward diffusion of Ni and Co is responsible for the formation and coalescence of first-stage single-grain oxide islands. The second-stage of oxidation involves the formation and coalescence of poly-grain oxide islands.

Elastomer surfaces with directionally dependent adhesion strength and their use in transfer printing with continuous roll-to-roll applications.

In this paper we present mechanics and materials aspects of elastomeric stamps that have angled features of relief on their surfaces, designed to enable control of adhesion strength by peeling direction, in a way that can be exploited in schemes for deterministic assembly by transfer printing. Detailed mechanics models capture the essential physics of interface adhesion in this system. Experiments with cylindrical stamps that have this design demonstrate their potential for use in a continuous, roller mode of operation.